Matrix factorization algorithms help track neuronal activity They then excited the beads using blue laser light and collected the resulting fluorescence speckles using first a microscope objective and ...

Matrix factorization techniques have become pivotal in data mining, enabling the extraction of latent structures from large-scale data matrices. These methods decompose complex datasets into lower ...

We describe here the use of nonnegative matrix factorization (NMF), an algorithm based on decomposition by parts that can reduce the dimension of expression data from thousands of genes to a handful ...

New research from the Wisconsin Institute for Discovery is tackling a complex packing problem. Thanks to the development of a powerful new computational tool introduced in a study published earlier ...

Matrix factorization in numerical linear algebra (NLA) typically serves the purpose of restating some given problem in such a way that it can be solved more readily; for example, one major application ...